Who are the partners in QoLEAD?

QoLEAD is a collaboration between seventeen research institutions, healthcare organisations and social organisations.

QoLEAD is funded by NWO (Living with Dementia Programme), ZonMw (Dementia Research Programme) and Alzheimer Nederland. The name of the consortium stands for Quality of Life through the use of Enabling AI in Dementia.

Who’s who?

Prof. Dr Wijnand IJsselsteijn is the Principal Investigator of QoLEAD and leads the consortium. The research is divided into seven work packages, led by:

1. Prof. Dr Wijnand IJsselsteijn (Eindhoven University of Technology, EUT)
2. Prof. Dr Ir Rens Brankaert (EUT)
3. Prof. Marjolein de Vugt, Maastricht University
4. Prof. Dr Debby Gerritsen, Radboud UMC
5. Dr Roel Boumans and Tibor Bosse, Radboud University
6. Prof. Erik Buskens, UMCG and Ron Handels, Maastricht University
7. Prof. Dr Henk Herman Nap (Vilans and EUT) & Prof. Dr Alexander Peine, Open University of the Netherlands

Specialists in the fields of implementation, FAIR data and other activities that contribute to impact are represented amongst the collaboration partners.

You can find out more about the team at qolead.nl.

Collaborating partners

• Eindhoven University of Technology (TU/e), lead applicant
• Maastricht University
• Alzheimer Nederland
• Joint Artificial Intelligence Network (JAIN)
• Radboud University
• Delft University of Technology
• Groningen University Medical Centre (UMCG)
• Fontys University of Applied Sciences
• Rotterdam University of Applied Sciences
• Open University
• Vilans Knowledge Organisation
• Avoord Care Organisation
• Zonnehuis Group Amstelland
• Tante Louise Care Organisation
• SVRZ Service Centre (Care in Zeeland)
• Radboudumc
• Nijmegen University Knowledge Network for Elderly Care (UKON)

Visit Alzheimer Nederland.nl Find out more about the Dementia Research Programme at zonmw.nl.

You can find out more about the Living with Dementia Programme at nwo.nl.

Improving the quality of life for people with dementia through smart technology

Smart technology can make life more pleasant, safer and more meaningful for people with dementia. Provided that the technology reaches them and is tailored to the needs of everyone involved. In practice, this often goes wrong. QoLEAD wants to change that.

It is complex to involve people with dementia, AI experts, healthcare organisations, health insurers, advocacy groups and businesses, and to give them a say in the development of care and technology. QoLEAD aims to discover how to organise an effective ‘learning ecosystem for collaboration’. QoLEAD uses this knowledge in the development of various smart tools. QoLEAD organises all this research into seven work packages.

What is the impact of AI technology?

Developing AI healthcare technology is expensive. An important question is therefore: what benefits do they deliver? Do AI innovations do what they were designed to do? Do they do it well? Does quality of life improve? And does this reduce the demand for care? In other words: do people with dementia feel more independent, safer or less lonely as a result, over the long term? This is what QoLEAD is investigating.

How do you implement technology widely and sustainably in practice?

Many technologies are tested in pilot schemes but never make it into everyday practice. They get stuck in the testing phase. Why is that? And how do you ensure that smart solutions are indeed implemented widely and sustainably? To answer these questions, QoLEAD is investigating how to adapt technology for use in various (care) settings and situations.

Co-creation and co-design

QoLEAD is researching and working on co-creation and co-design. As part of the co-creation project, QoLEAD is exploring the best ways to organise collaboration with people from different disciplines and with different backgrounds. People with dementia (and their loved ones), AI technologists, innovation researchers and healthcare professionals have different prior knowledge, use different language, and have different interests and expectations. QoLEAD experiments with and analyses what is needed to foster mutual understanding and how to enable everyone to contribute ideas, take part in decision-making and work together.

In addition, QoLEAD works in co-design projects alongside stakeholders on the design, development and testing of care technology, within so-called design cycles. QoLEAD then utilises the results of both types of projects.

AI for assessing safety risks

QoLEAD is investigating how smart tools can be used to gain a better understanding of the health, safety and care needs of people with dementia. These tools help care professionals to provide appropriate support at the right time.

For example, people with dementia are sometimes at greater risk of a fall or other accident. Artificial intelligence (AI) is likely to help identify such risks in good time. QoLEAD is also developing apps and sensors that automatically monitor a person’s functioning, for example by tracking movement or mood.

AI to strengthen social connections

QoLEAD is also investigating whether (and how) AI can help reduce loneliness and strengthen social interaction – both at home and in care homes. For example, through AI-powered conversation partners or digital diaries that help remind you of appointments.

Loneliness and a lack of social contact significantly reduce a person’s well-being. This is particularly common amongst people with dementia. People with dementia tend to withdraw or find it difficult to make contact. And their loved ones often no longer have time for social contact due to the informal care they provide.

AI to enhance a sense of purpose and self-worth

As someone with dementia needs more help, becomes less able to make decisions, and no longer feels useful, their sense of control, self-esteem and a sense of purpose may diminish. QoLEAD is investigating whether AI can help in this regard. For example, in the form of a smart assistant (a robot or app) that suggests activities and helps to carry them out, tailored to a person’s interests. Such as listening to music together or reminiscing.

Applied and participatory research

QoLEAD carries out what is known as applied participatory research. The team develops and tests AI-supported care solutions in real-world settings, in collaboration with those involved.

QoLEAD is already working with people with dementia, their loved ones and healthcare professionals. QoLEAD will also actively involve businesses once it becomes clear which innovations show promise for commercialisation.

Analysis of problems and solutions

The participatory aspect lies in the fact that QoLEAD actively involves people with dementia, their loved ones and care providers in the various phases of the research. Initially, discussions take place to gain a clear understanding of their experiences, wishes and concerns.

These form the starting point for the design of new technologies, such as sleep aids or tools that provide informal carers with an overview. The designs are also discussed and adapted where necessary. QoLEAD then builds and tests a prototype.

AI data analysis for use in tools

Data analysis is essential for the development of AI technology. For example, QoLEAD is developing a tool to assess safety risks for people with dementia, with the help of AI. To this end, researchers have existing data analysed by AI programmes – such as reports from GPs and case managers.

Lab and practice: testing and refinement

Developed tools and other AI solutions are then tested in several rounds and continuously adapted (so-called design cycles). This is done, amongst other things, through workshops, in which people with dementia (and their carers) and other stakeholders actively contribute ideas and provide feedback.

Tests also take place in real-world settings, such as in a care home, a care training programme or at home (which QoLEAD refers to as ‘living labs’). For example, with a sensor that can detect a risk of falling, or with an app that helps maintain a daily routine. QoLEAD assesses whether something works from a technical perspective, but focuses primarily on whether it is practical and user-friendly. Does it feel comfortable? Does it genuinely help someone in real life?

Measuring impact: developing simulation models

The researchers are also working, with the help of AI, on a simulation model. This is ultimately intended to show the progression of dementia over a period of five to ten years. In particular, it will look at aspects such as changes in quality of life, social contact, self-esteem, a sense of purpose and care needs. Once the model is complete, it will be possible to predict the effect of specific care interventions, technologies or measures.

To measure the impact of the AI technologies being developed by QoLEAD, the consortium intends to bring together all the data, analyses and insights from these projects. And incorporate them into the simulation model. This includes questionnaires on quality of life, healthcare utilisation and the experiences of relatives, as well as input from experts and other existing models. The model should then be able to predict the extent to which the AI tools contribute to, amongst other things, quality of life and a reduction in healthcare costs.

Bespoke AI technology for healthcare, policy, education and science

QoLEAD delivers a range of knowledge products, from new tools to medical guidelines, for use by scientists, healthcare professionals, policymakers and teachers.

Effective AI-driven technologies

QoLEAD develops and tests new AI-based tools within three areas that have a major impact on quality of life: health & safety, social connection, and personal autonomy. These include smart technologies that make it easier to connect with others, detect risks in healthcare at an earlier stage and help people continue to engage in meaningful activities.

Guidelines, practical advice and input for education

QoLEAD will also draw up practical guidelines so that other relevant stakeholders can benefit from the QoLEAD findings. This will include practical guidance on involving people with dementia in technology development, as well as on ethics, privacy and user-friendliness when designing AI applications.

Furthermore, QoLEAD aims to develop implementation guidelines: what conditions need to be put in place so that healthcare practitioners can actually make use of a solution?

QoLEAD is still investigating how healthcare training programmes can benefit from its findings, and in what form QoLEAD should make these available.

Simulation models for impact

Healthcare must be effective, whilst also remaining affordable and sustainable. That is why QoLEAD is building a simulation model capable of predicting the extent to which a developed technology contributes to quality of life, and what it costs and saves in the long term. Such a model helps policymakers and healthcare organisations to make evidence-based decisions: which solutions are worth implementing more widely?

Learning and innovation network

To continue learning about co-creation and co-design, QoLEAD has established an open learning and innovation network. Within this ‘ecosystem’, researchers, healthcare organisations, practitioners and companies share experiences and insights. The network will continue to exist after the QoLEAD project has ended.

Scientific publications

Naturally, QoLEAD also publishes scientific articles on a regular basis. The articles below illustrate the scope of QoLEAD’s research. Please visit the QoLEAD website for further scientific publications.

Measuring stigma surrounding dementia

QoLEAD translated the Dementia Public Stigma Scale into Dutch and validated it. This enables us to measure stigma surrounding dementia in the Netherlands in a reliable and valid manner. This is an important step towards a better understanding of public perceptions and raising awareness of dementia. In new research, this stigma scale will be used to investigate which aspects public stigma is linked to and how perceptions can be improved.

Measuring dementia-related stigma in the Dutch general public: Translation and validation of the Dementia Public Stigma Scale. See LinkedIn.com (abstract) or read the full article at journals.sagepub.com

Determining the added value of technology

In practice, an increasing number of technological solutions are emerging for people with dementia and their carers. To determine whether these truly add value, QoLEAD developed a conceptual health economic model. This model illustrates how technological interventions can influence the progression of dementia, the transitions between care settings (home, home care, nursing home), the quality of life of people with dementia, and long-term care utilisation and costs.

Assessing technologies in dementia care: A conceptual health-economic model. See LinkedIn.com (abstract) or read the article at journals.sagepub.com.

Impact of AI assessed

Tailored technology can support people with dementia in living comfortably at home for longer and improve their quality of life. Artificial intelligence (AI) can contribute to this. However, the actual role that AI plays in the development of such support was unclear. QoLEAD therefore reviewed the scientific literature. This review shows that AI applications aimed at improving quality of life are still at an early stage of development. Research is largely limited to small-scale feasibility studies, with little active involvement of people with dementia themselves – and is not focused on demonstrating clinical effectiveness. QoLEAD concludes that, whilst AI is promising, further research and rigorous validation in practice are needed before AI can have a meaningful impact on the daily lives of people with dementia.

Use of artificial intelligence to support the quality of life of people with dementia: a scoping review. Read the full article on sciencedirect.com.

QoLEAD regularly shares experiences and updates

For recent publications and other news, visit qolead.nl. Would you like QoLEAD to keep you up to date?

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